code: def process_image(img):
      img = cv2.imread(img).astype("float32")
      img = cv2.resize(img, (in_size, in_size))
      img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
      img = torch.from_numpy(img / 255.0).permute(2, 0, 1).float()
      img = torch.unsqueeze(img, axis=0)
  
      return img
  
file_path: tvm/tests/python/frontend/pytorch/test_object_detection.py
imports: import numpy
  import cv2
  import torch
  import torchvision
  import tvm
  import tvm.testing
  from tvm import relay
  from tvm.runtime.vm import VirtualMachine
  from tvm.relay.frontend.pytorch_utils import rewrite_nms_to_batched_nms, rewrite_batched_nms_with_max_out_size, rewrite_scatter_to_gather
  from tvm.contrib.download import download
label_desc: Use image node_id 1 for calling a global function with example usage: process_image(img) and returns: img